GPU error when run sample code

[vachelch]

When I run the sample code, python examples/sample.py --train_path $TRAIN_PATH --dev_path $DEV_PATH

GPU errors appear as below, It seems data don't satisfy a gpu tensor, I failed to solve it. Has anyone meet the error, too?

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/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/functional.py:52: UserWarning: size_average and reduce args will be deprecated, please use reduction='elementwise_mean' instead. warnings.warn(warning.format(ret)) 2018-11-20 23:33:48,774 root INFO Namespace(dev_path='data/toy_reverse/dev/data.txt', expt_dir='./experiment', load_checkpoint=None, log_level='info', resume=False, train_path='data/toy_reverse/train/data.txt') /home/Vachel/env3/lib/python3.5/site-packages/torch/nn/functional.py:52: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead. warnings.warn(warning.format(ret)) /home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/rnn.py:38: UserWarning: dropout option adds dropout after all but last recurrent layer, so non-zero dropout expects num_layers greater than 1, but got dropout=0.2 and num_layers=1 "num_layers={}".format(dropout, num_layers)) 2018-11-20 23:33:51,817 seq2seq.trainer.supervised_trainer INFO Optimizer: Adam ( Parameter Group 0 amsgrad: False betas: (0.9, 0.999) eps: 1e-08 lr: 0.001 weight_decay: 0 ), Scheduler: None Traceback (most recent call last): File "examples/sample.py", line 129, in resume=opt.resume) File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/trainer/supervised_trainer.py", line 186, in train teacher_forcing_ratio=teacher_forcing_ratio) File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/trainer/supervised_trainer.py", line 103, in _train_epoches loss = self._train_batch(input_variables, input_lengths.tolist(), target_variables, model, teacher_forcing_ratio) File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/trainer/supervised_trainer.py", line 55, in _train_batch teacher_forcing_ratio=teacher_forcing_ratio) File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in call result = self.forward(*input, kwargs) File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/models/seq2seq.py", line 48, in forward encoder_outputs, encoder_hidden = self.encoder(input_variable, input_lengths) File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in call result = self.forward(*input, *kwargs) File "/home/Vachel/SDML/hw3-0/pytorch-seq2seq/seq2seq/models/EncoderRNN.py", line 68, in forward embedded = self.embedding(input_var) File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/module.py", line 477, in call result = self.forward(input, kwargs) File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/modules/sparse.py", line 110, in forward self.norm_type, self.scale_grad_by_freq, self.sparse) File "/home/Vachel/env3/lib/python3.5/site-packages/torch/nn/functional.py", line 1110, in embedding return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse) RuntimeError: Expected object of type torch.cuda.LongTensor but found type torch.LongTensor for argument #3 'index'

[pskrunner14]

@soHardToPickName please see #169.

[KevinMatrix]

@soHardToPickName please see #169.

your issue is not helpfule, I solve this by change "device = None if torch.cuda.is_available() else -1" to "device = torch.device("cuda" if torch.cuda.is_available() else "cpu")" in seq2seq/trainer/supervised_trainer.py:75

use this way also in seq2seq/evaluator/evaluator.py:38

[vachelch]

@soHardToPickName please see #169.

your issue is not helpfule, I solve this by change "device = None if torch.cuda.is_available() else -1" to "device = torch.device("cuda" if torch.cuda.is_available() else "cpu")" in seq2seq/trainer/supervised_trainer.py:75

use this way also in seq2seq/evaluator/evaluator.py:38

Thanks very much for your answer! this is just the solution, and sorry for reply late~

[xiaodaoyoumin]

good !